Ai Agents AI Agent Skills

The semantic engine for MCP clients. Define metrics once, query from anywhere. Docs · Getting Started · Changelog · Discord · Bonnard is an agent-native semantic layer CLI. Deploy an MCP server and governed analytics API in minutes -for AI agents, BI tools, and data teams. Define metrics and dimensions in YAML, validate locally, and ship to production. Works with Snowfl

:deciduoustree: MCPJungle :deciduoustree: Self-hosted MCP Gateway for your private AI agents MCPJungle is an open source, self-hosted Gateway for all your Model Context Protocol Servers. 🧑‍💻 Developers use it to register & manage MCP servers and the tools they provide from a central place. 🤖 MCP Clients use it to discover and consume all these tools from a single "Gateway" MCP Server. MCPJungle

Stateful agent-to-agent communication client for the agent:// protocol. AGENIUM provides identity, discovery, and messaging for AI agents. Think of it as DNS + HTTP for agents — each agent gets a unique agent://name URI and can discover and communicate with other agents. Choose from 3 templates: echo (hello world), tools (tool-calling), api (REST gateway). - agent:// Protocol — Unique agent identi

OMOPHub MCP Server Medical vocabularies for AI agents. Search, map, and navigate 10M+ OMOP concepts: SNOMED CT, ICD-10, RxNorm, LOINC, and more. Directly from Claude, Cursor, VS Code, or any MCP-compatible client. Quick Start · Examples · Working with medical vocabularies today means downloading multi-gigabyte CSV files, loading them into a local database, and writing SQL to find what you need. Ev

Contact us for a Demo Community Slack MindsDB enables humans, AI, agents, and applications to get highly accurate answers across large scale data sources. MindsDB is an open-source server that can be deployed anywhere - from your laptop to the cloud, and everywhere in between. And yes, you can customize it to your heart's content. Using Docker Desktop. This is the fastest and recommended way to ge

This is a Model Context Protocol (MCP) server that integrates AgentQL's data extraction capabilities. - extract-web-data - extract structured data from a given 'url', using 'prompt' as a description of actual data and its fields to extract. To use AgentQL MCP Server to extract data from web pages, you need to install it via npm, get an API key from our Dev Portal, and configure it in your favorite

Model Context Protocol server for TorrentClaw — giving AI assistants the ability to search movies and TV shows, find torrents with magnet links, check streaming availability, and explore cast/crew metadata. torrentclaw-mcp is developed by TorrentClaw as part of its open-source ecosystem. It wraps the TorrentClaw API into the MCP standard so that any compatible AI assistant (Claude, GPT, etc.) can

Use when the user wants to find, evaluate, audit, or install an open-source AI agent skill or MCP server — e.g. "find an MCP server for Postgres", "is this skill safe to install", "what should I use to scrape a website". Searches a quality-scored, security-graded catalog of ~20K skills locally (cached index, zero backend load) and returns each result's security grade, quality score, and install commands so you can check trust BEFORE installing.

Shodh-Memory Persistent memory for AI agents. Single binary. Local-first. Runs offline. We built this because AI agents forget everything between sessions. They make the same mistakes, ask the same questions, lose context constantly. Shodh-Memory fixes that. It's a cognitive memory system—Hebbian learning, activation decay, semantic consolidation—packed into a single ~17MB binary that runs offline

An MCP (Model Context Protocol) server that enables AI platforms to interact with YepCode's infrastructure. Run LLM generated scripts and turn your YepCode processes into powerful tools that AI assistants can use directly. - Seamless AI Integration: Convert YepCode processes into AI-ready tools with zero configuration - Real-time Process Control: Enable direct interaction between AI systems and yo

A Model Context Protocol server implementation for Last9 that enables AI agents to seamlessly bring real-time production context — logs, metrics, and traces — into your local environment to auto-fix code faster. - View demo announcement blog post - Installation - Configuration - Tools Documentation - Development You can connect to Last9 MCP in two ways: This is the easiest and cleanest setup. You

The Web, Readable. Your AI agent spends 60,000 tokens just to look at a web page. Charlotte does it in 336. Charlotte is an MCP server that gives AI agents structured, token-efficient access to the web. Instead of dumping the full accessibility tree on every call, Charlotte returns only what the agent needs: a compact page summary on arrival, targeted queries for specific elements, and full detail

cognee‑mcp - Run cognee’s memory engine as a Model Context Protocol server Join Discord Join r/AIMemory Build memory for Agents and query from any client that speaks MCP – in your terminal or IDE. - Multiple transports – choose Streamable HTTP --transport http (recommended for web deployments), SSE --transport sse (real‑time streaming), or stdio (classic pipe, default) - API Mode – connect to an a

Watch AG-UI + LangChain demo - SSE - Server-Sent Events for connection state and observability updates - Flexible Storage - Redis, SQLite, File System, or In-Memory backends - Serverless - Works in serverless environments (Vercel, AWS Lambda, etc.) - React Hook - useMcp hook for easy React integration - Vue Composable - useMcp composable for Vue applications - MCP Protocol - Support for tools, pro

An AI coding assistant built in Rust that provides both command-line and graphical interfaces for autonomous code analysis and modification. Multi-Modal Tool Execution: Adapts to different LLM capabilities with pluggable tool invocation modes - native function calling, XML-style tags, and triple-caret blocks - ensuring compatibility across various AI providers. Real-Time Streaming Interface: Advan

Your MCPs, supercharged. Find any tool instantly, execute with code mode, run on schedule, discover skills, load Photons, ready for any client. Smart loading saves tokens and energy. Instead of your AI juggling 50+ tools scattered across different MCPs, NCP gives it a single, unified interface with code mode execution, scheduling, skills discovery, and custom Photons. Your AI sees just 2-3 simple

The Web MCP 🌐 Give your AI real-time web superpowers Seamlessly connect LLMs to the live web without getting blocked Quick Start • Features • 🎉 Free Tier Available! 🎉 5,000 requests/month FREE Perfect for prototyping and everyday AI workflows 🚀 Launch Week - January 2026 🚀 5 Days of Major Releases! 📦 Tool Groups 🧙 Setup Wizard ⚡ Token Efficiency 🏢 Enterprise Integrations 📊 Observability

The memory system for AI coding agents. Decisions, lessons, and context that persist across sessions. mcp-name: io.github.omega-memory/omega-memory AI coding agents are stateless. Every new session starts from zero. - Context loss. Agents forget every decision, preference, and architectural choice between sessions. Developers spend 10-30 minutes per session re-explaining context that was already e

DevDocs-MCP is a Model Context Protocol (MCP) server that provides version-pinned, deterministic documentation sourced from DevDocs.io to AI assistants (Claude, RooCode, Cline, Copilot etc.). It acts as a local Documentation Intelligence Layer, ensuring your agent always has the correct API context without network latency or training data drift. This server follows the proposed MCP server standard

Update properties or content across many pages in a Notion database with dry-run and error recovery

You can run the MCP Server in a Docker container. This is useful if you want to avoid managing Python environments or dependencies on your local machine. See kestramcpdocker. Paste the following configuration into your MCP settings (e.g., Cursor, Claude, or VS Code): - Replace , , and with your actual credentials. - For OSS installations, you can use KESTRAUSERNAME and KESTRAPASSWORD instead of KE

deco Studio Open-source · TypeScript-first · Deploy anywhere Open-source private AI workspace for organizations. decocms.com/studio Studio packages the infrastructure behind an internal AI rollout: model routing, MCP authentication, agent configuration, SSO, RBAC, audit logs, and usage accounting. Your teams get chat. You keep control. Under the hood it's one control plane for your AI agents — one

Scrape, crawl, search, and extract web data. Converts any website to LLM-ready markdown. Local-first with smart escalation (HTTP → browser → stealth). No API key needed.